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未验证 提交 16315d3d 编写于 作者: C Chen Weihang 提交者： GitHub
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Delete Ref & VectorRef and add GetDataSafely (#22997) 

* delete invalid check inferface Ref & VectorRef, test=develop

* fix vector ref delete error, test=develop

* try the new check inferface, test=develop

* change all related code with new check macro, test=develop

* remove static assert, test=develop

* polish detail, test=develop

* skip coverage problem, test=develop

* add new check macro, test=develop
上级 4c675a45
隐藏空白更改
内联 并排
Showing with 286 addition and 260 deletion
paddle/fluid/operators/activation_cudnn.cu.cc
浏览文件 @ 16315d3d
......@@ -31,8 +31,8 @@ class CudnnActivationKernel
ExtractActivationTensor(context, X, Out);
ActivationDescriptor act_desc;
TensorDescriptor x_desc, out_desc;
x_desc.set(detail::Ref(X));
out_desc.set(detail::Ref(Out));
x_desc.set(GET_DATA_SAFELY(X, "Input", "X", "CudnnActivation"));
out_desc.set(GET_DATA_SAFELY(Out, "Output", "Out", "CudnnActivation");
}
};
......
paddle/fluid/operators/activation_cudnn_op.cu.cc
浏览文件 @ 16315d3d
......@@ -37,7 +37,7 @@ struct CudnnActivationFunctor {
act_desc.set(mode_, coef_);
TensorDescriptor x_desc, out_desc;
x_desc.set(x);
out_desc.set(detail::Ref(out));
out_desc.set(GET_DATA_SAFELY(out, "Output", "Out", "CudnnActivation"));
PADDLE_ENFORCE(platform::dynload::cudnnActivationForward(
ctx_.cudnn_handle(), act_desc.desc(),
platform::CudnnDataType<T>::kOne(), x_desc.desc(), x.data<T>(),
......@@ -63,7 +63,7 @@ struct CudnnActivationGradFunctor {
x_desc.set(x);
out_desc.set(out);
dout_desc.set(dout);
dx_desc.set(detail::Ref(dx));
dx_desc.set(GET_DATA_SAFELY(dx, "Output", "X@GRAD", "CudnnActivationGrad"));
PADDLE_ENFORCE(platform::dynload::cudnnActivationBackward(
ctx_.cudnn_handle(), act_desc.desc(),
platform::CudnnDataType<T>::kOne(), out_desc.desc(), out.data<T>(),
......@@ -141,7 +141,7 @@ class CudnnActivationKernel
Out->mutable_data<T>(context.GetPlace());
auto& dev_ctx = context.template device_context<CUDADeviceContext>();
Functor functor(dev_ctx);
functor(detail::Ref(X), Out);
functor(GET_DATA_SAFELY(X, "Input", "X", "CudnnActivation"), Out);
}
};
......@@ -161,7 +161,10 @@ class CudnnActivationGradKernel
dX->mutable_data<T>(context.GetPlace());
auto& dev_ctx = context.template device_context<CUDADeviceContext>();
Functor functor(dev_ctx);
functor(detail::Ref(X), detail::Ref(Out), detail::Ref(dOut), dX);
functor(GET_DATA_SAFELY(X, "Input", "X", "CudnnActivationGrad"),
GET_DATA_SAFELY(Out, "Input", "Out", "CudnnActivationGrad"),
GET_DATA_SAFELY(dOut, "Input", "Out@GRAD", "CudnnActivationGrad"),
dX);
}
};
......
paddle/fluid/operators/activation_op.h
浏览文件 @ 16315d3d
......@@ -26,7 +26,6 @@ limitations under the License. */
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/math/blas.h"
#include "paddle/fluid/platform/float16.h"
......@@ -156,8 +155,10 @@ class ActivationKernel
ExtractActivationTensor(context, &X, &Out);
Out->mutable_data<T>(context.GetPlace());
auto x = framework::EigenVector<T>::Flatten(detail::Ref(X));
auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto x = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(X, "Input", "X", "Activation"));
auto out = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(Out, "Output", "Out", "Activation"));
auto* place =
context.template device_context<DeviceContext>().eigen_device();
Functor functor;
......@@ -182,10 +183,14 @@ class ActivationGradKernel
ExtractActivationGradTensor<Functor::FwdDeps()>(context, &X, &Out, &dOut,
&dX);
dX->mutable_data<T>(context.GetPlace());
auto dout = framework::EigenVector<T>::Flatten(detail::Ref(dOut));
auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto dx = framework::EigenVector<T>::Flatten(detail::Ref(dX));
auto x = framework::EigenVector<T>::Flatten(detail::Ref(X));
auto dout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dOut, "Input", "Out@GRAD", "ActivationGrad"));
auto out = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(Out, "Input", "Out", "ActivationGrad"));
auto dx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dX, "Input", "X@GRAD", "ActivationGrad"));
auto x = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(X, "Input", "X", "ActivationGrad"));
auto* place =
context.template device_context<DeviceContext>().eigen_device();
Functor functor;
......@@ -1285,10 +1290,13 @@ struct ReluGradGradFunctor : public BaseActivationFunctor<T> {
framework::Tensor* ddOut, framework::Tensor* dOut,
framework::Tensor* dX) const {
auto* d = dev.eigen_device();
auto ddx = framework::EigenVector<T>::Flatten(detail::Ref(ddX));
auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto ddx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddX, "Input", "DDX", "ReluGradGrad"));
auto out = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(Out, "Output", "Out", "ReluGradGrad"));
if (ddOut) {
auto ddout = framework::EigenVector<T>::Flatten(detail::Ref(ddOut));
auto ddout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddOut, "Output", "DDOut", "ReluGradGrad"));
ddout.device(*d) = ddx * (out > static_cast<T>(0)).template cast<T>();
}
}
......@@ -1308,9 +1316,12 @@ struct LeakyReluGradGradFunctor : public BaseActivationFunctor<T> {
framework::Tensor* dX) const {
if (ddOut) {
auto* d = dev.eigen_device();
auto ddx = framework::EigenVector<T>::Flatten(detail::Ref(ddX));
auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto ddout = framework::EigenVector<T>::Flatten(detail::Ref(ddOut));
auto ddx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddX, "Input", "DDX", "LeakyReluGradGrad"));
auto out = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(Out, "Output", "Out", "LeakyReluGradGrad"));
auto ddout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddOut, "Output", "DOut", "LeakyReluGradGrad"));
ddout.device(*d) = ddx *
((out > static_cast<T>(0)).template cast<T>() +
static_cast<T>(alpha) *
......@@ -1332,18 +1343,23 @@ struct ELUGradGradFunctor : public BaseActivationFunctor<T> {
const framework::Tensor* ddX, framework::Tensor* ddOut,
const framework::Tensor* dOut, framework::Tensor* dX) const {
auto* d = dev.eigen_device();
auto ddx = framework::EigenVector<T>::Flatten(detail::Ref(ddX));
auto x = framework::EigenVector<T>::Flatten(detail::Ref(X));
auto ddx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddX, "Input", "DDX", "ELUGradGrad"));
auto x = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(X, "Input", "X", "ELUGradGrad"));
if (dX) {
auto dx = framework::EigenVector<T>::Flatten(detail::Ref(dX));
auto dout = framework::EigenVector<T>::Flatten(detail::Ref(dOut));
auto dx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dX, "Output", "DX", "ELUGradGrad"));
auto dout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dOut, "Output", "DOut", "ELUGradGrad"));
dx.device(*d) = ddx * dout * static_cast<T>(alpha) * x.exp() *
(x < static_cast<T>(0)).template cast<T>();
}
if (ddOut) {
auto ddout = framework::EigenVector<T>::Flatten(detail::Ref(ddOut));
auto ddout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddOut, "Output", "DDOut", "ELUGradGrad"));
ddout.device(*d) = ddx *
((x > static_cast<T>(0)).template cast<T>() +
static_cast<T>(alpha) * x.exp() *
......@@ -1361,17 +1377,22 @@ struct SqrtGradGradFunctor : public BaseActivationFunctor<T> {
const framework::Tensor* ddX, framework::Tensor* ddOut,
framework::Tensor* dOut, const framework::Tensor* dX) const {
auto* d = dev.eigen_device();
auto ddx = framework::EigenVector<T>::Flatten(detail::Ref(ddX));
auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto ddx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddX, "Input", "DDX", "SqrtGradGrad"));
auto out = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(Out, "Output", "Out", "SqrtGradGrad"));
// sqrt GradGrad: ddy = 0.5 * ddx / y, dy = -1 * dx * ddx
// calculate dy first, so ddy can inplace ddx
if (dOut) {
auto dx = framework::EigenVector<T>::Flatten(detail::Ref(dX));
auto dout = framework::EigenVector<T>::Flatten(detail::Ref(dOut));
auto dx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dX, "Output", "DX", "SqrtGradGrad"));
auto dout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dOut, "Output", "DOut", "SqrtGradGrad"));
dout.device(*d) = dx * ddx * static_cast<T>(-1) / out;
}
if (ddOut) {
auto ddout = framework::EigenVector<T>::Flatten(detail::Ref(ddOut));
auto ddout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddOut, "Output", "DDOut", "SqrtGradGrad"));
ddout.device(*d) = ddx * static_cast<T>(0.5) / out;
}
}
......@@ -1385,17 +1406,22 @@ struct SquareGradGradFunctor : public BaseActivationFunctor<T> {
const framework::Tensor* ddX, framework::Tensor* ddOut,
const framework::Tensor* dOut, framework::Tensor* dX) const {
auto* d = dev.eigen_device();
auto ddx = framework::EigenVector<T>::Flatten(detail::Ref(ddX));
auto x = framework::EigenVector<T>::Flatten(detail::Ref(X));
auto ddx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddX, "Input", "DDX", "SquareGradGrad"));
auto x = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(X, "Input", "X", "SquareGradGrad"));
// square GradGrad: ddy=2x*ddx, dx=2dy*ddx
// calculate dx first, so ddy can inplace ddx
if (dX) {
auto dx = framework::EigenVector<T>::Flatten(detail::Ref(dX));
auto dout = framework::EigenVector<T>::Flatten(detail::Ref(dOut));
auto dx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dX, "Output", "DX", "SquareGradGrad"));
auto dout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dOut, "Output", "DOut", "SquareGradGrad"));
dx.device(*d) = ddx * static_cast<T>(2) * dout;
}
if (ddOut) {
auto ddout = framework::EigenVector<T>::Flatten(detail::Ref(ddOut));
auto ddout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(ddOut, "Output", "DDOut", "SquareGradGrad"));
ddout.device(*d) = ddx * static_cast<T>(2) * x;
}
}
......@@ -1557,8 +1583,10 @@ class PowKernel : public framework::OpKernel<typename Functor::ELEMENT_TYPE> {
ExtractActivationTensor(context, &X, &Out);
Out->mutable_data<T>(context.GetPlace());
auto x = framework::EigenVector<T>::Flatten(detail::Ref(X));
auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto x = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(X, "Input", "X", "Pow"));
auto out = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(Out, "Output", "Out", "Pow"));
auto* place =
context.template device_context<DeviceContext>().eigen_device();
Functor functor;
......@@ -1602,10 +1630,14 @@ class PowGradKernel
ExtractActivationGradTensor<Functor::FwdDeps()>(context, &X, &Out, &dOut,
&dX);
dX->mutable_data<T>(context.GetPlace());
auto dout = framework::EigenVector<T>::Flatten(detail::Ref(dOut));
auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto dx = framework::EigenVector<T>::Flatten(detail::Ref(dX));
auto x = framework::EigenVector<T>::Flatten(detail::Ref(X));
auto dout = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dOut, "Input", "Out@GRAD", "PowGrad"));
auto out = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(Out, "Input", "Out", "PowGrad"));
auto dx = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(dX, "Output", "X@GRAD", "PowGrad"));
auto x = framework::EigenVector<T>::Flatten(
GET_DATA_SAFELY(X, "Input", "X", "PowGrad"));
auto* place =
context.template device_context<DeviceContext>().eigen_device();
Functor functor;
......
paddle/fluid/operators/add_position_encoding_op.h
浏览文件 @ 16315d3d
......@@ -15,7 +15,6 @@ limitations under the License. */
#pragma once
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/controlflow/get_places_op.cc
浏览文件 @ 16315d3d
......@@ -14,7 +14,6 @@ limitations under the License. */
#include <thread> // NOLINT
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/platform/place.h"
#ifdef PADDLE_WITH_CUDA
#include "paddle/fluid/platform/gpu_info.h"
......@@ -56,10 +55,9 @@ class GetPlacesOp : public framework::OperatorBase {
is_gpu ? "GPU" : "CPU");
auto out_var_name = Output("Out");
auto &places =
*(detail::Ref(scope.FindVar(out_var_name),
"Output variable %s cannot be found", out_var_name)
.GetMutable<platform::PlaceList>());
auto &places = *(GET_DATA_SAFELY(scope.FindVar(out_var_name), "Output",
"Out", "GetPlaces")
.GetMutable<platform::PlaceList>());
places.reserve(device_count);
if (is_gpu) {
PADDLE_ENFORCE_LE(device_count, CUDADevCount(),
......
paddle/fluid/operators/controlflow/tensor_array_read_write_op.cc
浏览文件 @ 16315d3d
......@@ -12,7 +12,6 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/array_operator.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/math/math_function.h"
namespace paddle {
......
paddle/fluid/operators/controlflow/while_op.cc
浏览文件 @ 16315d3d
......@@ -19,7 +19,6 @@
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/framework/var_type.h"
#include "paddle/fluid/operators/controlflow/while_op_helper.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
namespace paddle {
namespace operators {
......@@ -198,23 +197,18 @@ class WhileGradOp : public framework::OperatorBase {
continue;
}
auto &og_outside =
detail::Ref(scope.FindVar(outside_og_name),
"Cannot find Outside Gradient %s", outside_og_name);
auto &og_inside =
detail::Ref(cur_scope.Var(inside_og_name),
"Cannot find inside gradient %s", inside_og_name);
auto &og_outside = *scope.FindVar(outside_og_name);
auto &og_inside = *cur_scope.Var(inside_og_name);
if (og_outside.IsType<framework::LoDTensor>()) {
auto &outside_tensor = og_outside.Get<framework::LoDTensor>();
auto &inside_tensor =
detail::Ref(og_inside.GetMutable<framework::LoDTensor>());
auto &inside_tensor = *og_inside.GetMutable<framework::LoDTensor>();
inside_tensor.set_lod(outside_tensor.lod());
inside_tensor.ShareDataWith(outside_tensor);
} else if (og_outside.IsType<framework::LoDTensorArray>()) {
auto outside_array =
og_outside.GetMutable<framework::LoDTensorArray>();
auto &inside_array =
detail::Ref(og_inside.GetMutable<framework::LoDTensorArray>());
*og_inside.GetMutable<framework::LoDTensorArray>();
inside_array.clear();
inside_array.resize(outside_array->size());
VLOG(8) << outside_og_name << " size = " << outside_array->size();
......
paddle/fluid/operators/conv_op.h
浏览文件 @ 16315d3d
......@@ -20,7 +20,6 @@ limitations under the License. */
#include <vector>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/math/blas.h"
#include "paddle/fluid/operators/math/depthwise_conv.h"
#include "paddle/fluid/operators/math/im2col.h"
......@@ -674,9 +673,8 @@ class GemmConvDoubleGradKernel : public framework::OpKernel<T> {
Tensor* ddY = ctx.Output<Tensor>("DDOutput");
Tensor* dW = ctx.Output<Tensor>("DFilter");
Tensor* dX = ctx.Output<Tensor>("DInput");
Tensor W = detail::Ref(ctx.Input<Tensor>("Filter"),
"Cannot find input Filter(%s) in scope)",
ctx.InputNames("Filter")[0]);
Tensor W = GET_DATA_SAFELY(ctx.Input<Tensor>("Filter"), "Input", "Filter",
"GemmConvDoubleGrad");
if (!ddY && !dW && !dX) return;
const int groups = ctx.Attr<int>("groups");
......
paddle/fluid/operators/cum_op.h
浏览文件 @ 16315d3d
......@@ -18,7 +18,6 @@ limitations under the License. */
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
namespace paddle {
namespace operators {
......@@ -29,13 +28,11 @@ class CumKernel : public framework::OpKernel<typename Functor::ELEMENT_TYPE> {
using T = typename Functor::ELEMENT_TYPE;
void Compute(const framework::ExecutionContext& context) const override {
auto& X = detail::Ref(context.Input<framework::Tensor>("X"),
"Cannot get input tensor X, variable name = %s",
context.InputName("X"));
auto& X = GET_DATA_SAFELY(context.Input<framework::Tensor>("X"), "Input",
"X", "Cum");
auto& Out = detail::Ref(context.Output<framework::Tensor>("Out"),
"Cannot get output tensor Out, variable name = %s",
context.OutputName("Out"));
auto& Out = GET_DATA_SAFELY(context.Output<framework::Tensor>("Out"),
"Output", "Out", "Cum");
int axis = context.Attr<int>("axis");
bool exclusive = context.Attr<bool>("exclusive");
bool reverse = context.Attr<bool>("reverse");
......@@ -46,7 +43,7 @@ class CumKernel : public framework::OpKernel<typename Functor::ELEMENT_TYPE> {
PADDLE_ENFORCE_LT(
axis, x_dims.size(),
"axis should be less than the dimensiotn of the input tensor");
Out.mutable_data<T>(context.GetPlace());
Out.template mutable_data<T>(context.GetPlace());
int pre = 1;
int post = 1;
......
paddle/fluid/operators/detail/safe_ref.h 已删除 100644 → 0
浏览文件 @ 4c675a45
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <vector>
#include "paddle/fluid/platform/enforce.h"
namespace paddle {
namespace operators {
namespace detail {
/**
* Get Reference From Pointer with check. The error message is printf format,
* and passed by `args`
*/
template <typename T, typename... ARGS>
inline T& Ref(T* ptr, ARGS&&... args) {
PADDLE_ENFORCE_NOT_NULL(ptr, ::paddle::string::Sprintf(args...));
return *ptr;
}
template <typename T, typename... ARGS>
inline std::vector<std::reference_wrapper<T>> VectorRef(
const std::vector<T*>& vec, ARGS&&... args) {
std::vector<std::reference_wrapper<T>> result;
result.reserve(vec.size());
for (auto* ptr : vec) {
result.emplace_back(Ref(ptr, args...));
}
return result;
}
} // namespace detail
} // namespace operators
} // namespace paddle
paddle/fluid/operators/detection/collect_fpn_proposals_op.h
浏览文件 @ 16315d3d
......@@ -20,7 +20,6 @@ limitations under the License.*/
#include <string>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/gather.h"
#include "paddle/fluid/operators/math/math_function.h"
......
paddle/fluid/operators/detection/distribute_fpn_proposals_op.h
浏览文件 @ 16315d3d
......@@ -20,7 +20,6 @@ limitations under the License. */
#include <string>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/gather.h"
#include "paddle/fluid/operators/math/math_function.h"
......
paddle/fluid/operators/detection/generate_proposals_op.cc
浏览文件 @ 16315d3d
......@@ -17,7 +17,6 @@ limitations under the License. */
#include <string>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/gather.h"
#include "paddle/fluid/operators/math/math_function.h"
......@@ -293,12 +292,10 @@ class GenerateProposalsKernel : public framework::OpKernel<T> {
auto *scores = context.Input<Tensor>("Scores");
auto *bbox_deltas = context.Input<Tensor>("BboxDeltas");
auto *im_info = context.Input<Tensor>("ImInfo");
auto anchors = detail::Ref(context.Input<Tensor>("Anchors"),
"Cannot find input Anchors(%s) in scope",
context.InputNames("Anchors")[0]);
auto variances = detail::Ref(context.Input<Tensor>("Variances"),
"Cannot find input Variances(%s) in scope",
context.InputNames("Variances")[0]);
auto anchors = GET_DATA_SAFELY(context.Input<Tensor>("Anchors"), "Input",
"Anchors", "GenerateProposals");
auto variances = GET_DATA_SAFELY(context.Input<Tensor>("Variances"),
"Input", "Variances", "GenerateProposals");
auto *rpn_rois = context.Output<LoDTensor>("RpnRois");
auto *rpn_roi_probs = context.Output<LoDTensor>("RpnRoiProbs");
......
paddle/fluid/operators/detection/generate_proposals_op.cu
浏览文件 @ 16315d3d
......@@ -20,7 +20,6 @@ limitations under the License. */
#include "paddle/fluid/framework/mixed_vector.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/memory/memory.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/gather.cu.h"
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/platform/for_range.h"
......@@ -367,12 +366,10 @@ class CUDAGenerateProposalsKernel : public framework::OpKernel<T> {
auto *scores = context.Input<Tensor>("Scores");
auto *bbox_deltas = context.Input<Tensor>("BboxDeltas");
auto *im_info = context.Input<Tensor>("ImInfo");
auto anchors = detail::Ref(context.Input<Tensor>("Anchors"),
"Cannot find input Anchors(%s) in scope",
context.InputNames("Anchors")[0]);
auto variances = detail::Ref(context.Input<Tensor>("Variances"),
"Cannot find input Variances(%s) in scope",
context.InputNames("Variances")[0]);
auto anchors = GET_DATA_SAFELY(context.Input<Tensor>("Anchors"), "Input",
"Anchors", "GenerateProposals");
auto variances = GET_DATA_SAFELY(context.Input<Tensor>("Variances"),
"Input", "Variances", "GenerateProposals");
auto *rpn_rois = context.Output<LoDTensor>("RpnRois");
auto *rpn_roi_probs = context.Output<LoDTensor>("RpnRoiProbs");
......
paddle/fluid/operators/fill_op.h
浏览文件 @ 16315d3d
......@@ -19,7 +19,6 @@ limitations under the License. */
#include <algorithm>
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
namespace paddle {
namespace operators {
......@@ -44,10 +43,8 @@ template <typename T>
class FillKernel : public framework::OpKernel<T> {
public:
void Compute(const paddle::framework::ExecutionContext &ctx) const override {
auto &out =
detail::Ref(ctx.Output<framework::LoDTensor>("Out"),
"Cannot get output lod tensor Out, variable name = %s",
ctx.OutputName("Out"));
auto &out = GET_DATA_SAFELY(ctx.Output<framework::LoDTensor>("Out"),
"Output", "Out", "Fill");
out.Resize(framework::make_ddim(ctx.Attr<std::vector<int>>("shape")));
auto dtype =
static_cast<framework::proto::VarType::Type>(ctx.Attr<int>("dtype"));
......
paddle/fluid/operators/fused/fused_elemwise_activation_op.h
浏览文件 @ 16315d3d
......@@ -18,7 +18,6 @@ limitations under the License. */
#include <vector>
#include "paddle/fluid/framework/op_desc.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/elementwise/elementwise_op_function.h"
#include "paddle/fluid/operators/math/compound_functors.h"
#include "paddle/fluid/operators/math/functors.h"
......@@ -383,12 +382,10 @@ template <typename DeviceContext, typename T>
class FusedElemwiseActivationKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext &ctx) const override {
auto &in_x = detail::Ref(ctx.Input<framework::Tensor>("X"),
"Cannot get input tensor %s, variable name = %s",
"X", ctx.InputName("X"));
auto &in_y = detail::Ref(ctx.Input<framework::Tensor>("Y"),
"Cannot get input tensor %s, variable name = %s",
"Y", ctx.InputName("Y"));
auto &in_x = GET_DATA_SAFELY(ctx.Input<framework::Tensor>("X"), "Input",
"X", "FusedElemwiseActivation");
auto &in_y = GET_DATA_SAFELY(ctx.Input<framework::Tensor>("Y"), "Input",
"Y", "FusedElemwiseActivation");
PADDLE_ENFORCE(ctx.HasOutput("Out"), "The output(Out) should not be empty");
auto output = ctx.Output<framework::Tensor>("Out");
......
paddle/fluid/operators/fused/fused_embedding_eltwise_layernorm_op.cc
浏览文件 @ 16315d3d
......@@ -14,7 +14,6 @@ limitations under the License. */
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/platform/errors.h"
namespace paddle {
......
paddle/fluid/operators/fused/fused_embedding_eltwise_layernorm_op.cu
浏览文件 @ 16315d3d
......@@ -19,7 +19,6 @@
#include "paddle/fluid/framework/framework.pb.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/memory/malloc.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/math/bert_encoder_functor.h"
#include "paddle/fluid/operators/math/blas.h"
......
paddle/fluid/operators/fused/multihead_matmul_op.cc
浏览文件 @ 16315d3d
......@@ -14,7 +14,6 @@ limitations under the License. */
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/platform/errors.h"
namespace paddle {
......
paddle/fluid/operators/fused/multihead_matmul_op.cu
浏览文件 @ 16315d3d
......@@ -17,7 +17,6 @@
#include <algorithm>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/memory/malloc.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/math/bert_encoder_functor.h"
#include "paddle/fluid/operators/math/blas.h"
......@@ -142,14 +141,13 @@ class MultiHeadMatMulV2Kernel : public framework::OpKernel<T> {
auto *input = context.Input<framework::Tensor>("Input");
auto *w = context.Input<framework::Tensor>("W");
auto *bias = context.Input<framework::Tensor>("Bias");
auto &bias_qk = detail::Ref(context.Input<framework::Tensor>("BiasQK"),
"Cannot find QK");
auto &bias_qk = GET_DATA_SAFELY(context.Input<framework::Tensor>("BiasQK"),
"Input", "BiasQK", "MultiHeadMatMulV2");
auto *input_d = input->data<T>();
auto *w_d = w->data<T>();
auto *bias_d = bias->data<T>();
auto *bias_qk_d = bias_qk.data<T>();
auto *bias_qk_d = bias_qk.template data<T>();
T scale = static_cast<T>(context.Attr<float>("alpha"));
int head_number = context.Attr<int>("head_number");
......
paddle/fluid/operators/hierarchical_sigmoid_op.h
浏览文件 @ 16315d3d
......@@ -24,7 +24,6 @@ limitations under the License. */
#include "paddle/fluid/framework/mixed_vector.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/clip_op.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/operators/math/matrix_bit_code.h"
#include "paddle/fluid/platform/transform.h"
......@@ -40,8 +39,9 @@ template <typename T, int MajorType = Eigen::RowMajor,
typename IndexType = Eigen::DenseIndex>
using EigenMatrix = framework::EigenMatrix<T, MajorType, IndexType>;
using platform::Transform;
using framework::LoDTensor;
static std::vector<int64_t> PathToRows(const framework::LoDTensor& path) {
static std::vector<int64_t> PathToRows(const LoDTensor& path) {
std::set<int64_t> rows;
const int64_t* paths = path.data<int64_t>();
for (int64_t i = 0; i < path.numel(); ++i) {
......@@ -57,14 +57,17 @@ template <typename DeviceContext, typename T>
class HierarchicalSigmoidOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
auto& in = detail::Ref(ctx.Input<framework::LoDTensor>("X"));
auto& w = detail::Ref(ctx.Input<framework::LoDTensor>("W"));
auto* path = ctx.Input<framework::LoDTensor>("PathTable");
auto* code = ctx.Input<framework::LoDTensor>("PathCode");
auto& label = detail::Ref(ctx.Input<framework::LoDTensor>("Label"));
auto* bias = ctx.Input<framework::LoDTensor>("Bias");
auto* out = ctx.Output<framework::LoDTensor>("Out");
auto* pre_out = ctx.Output<framework::LoDTensor>("PreOut");
auto& in = GET_DATA_SAFELY(ctx.Input<LoDTensor>("X"), "Input", "X",
"HierarchicalSigmoid");
auto& w = GET_DATA_SAFELY(ctx.Input<LoDTensor>("W"), "Input", "W",
"HierarchicalSigmoid");
auto* path = ctx.Input<LoDTensor>("PathTable");
auto* code = ctx.Input<LoDTensor>("PathCode");
auto& label = GET_DATA_SAFELY(ctx.Input<LoDTensor>("Label"), "Input",
"Label", "HierarchicalSigmoid");
auto* bias = ctx.Input<LoDTensor>("Bias");
auto* out = ctx.Output<LoDTensor>("Out");
auto* pre_out = ctx.Output<LoDTensor>("PreOut");
size_t num_classes = static_cast<size_t>(ctx.Attr<int>("num_classes"));
// for remote prefetch
......@@ -75,7 +78,7 @@ class HierarchicalSigmoidOpKernel : public framework::OpKernel<T> {
int64_t code_length =
path ? path->dims()[1] : math::FindLastSet(num_classes - 1);
int64_t batch_size = in.dims()[0];
framework::LoDTensor sum;
LoDTensor sum;
auto& dev_ctx = ctx.template device_context<DeviceContext>();
auto* pre_out_data = pre_out->mutable_data<T>(
framework::make_ddim({batch_size, code_length}), ctx.GetPlace());
......@@ -89,11 +92,11 @@ class HierarchicalSigmoidOpKernel : public framework::OpKernel<T> {
std::unique_ptr<math::MatrixBitCodeFunctor<T>> bit_code;
if (!is_custom) {
bit_code.reset(new math::MatrixBitCodeFunctor<T>(num_classes,
label.data<int64_t>()));
bit_code.reset(new math::MatrixBitCodeFunctor<T>(
num_classes, label.template data<int64_t>()));
} else {
bit_code.reset(new math::MatrixBitCodeFunctor<T>(*path, *code,
label.data<int64_t>()));
bit_code.reset(new math::MatrixBitCodeFunctor<T>(
*path, *code, label.template data<int64_t>()));
}
std::vector<int64_t> sum_dims({batch_size, 1UL});
......@@ -126,20 +129,24 @@ template <typename DeviceContext, typename T>
class HierarchicalSigmoidGradOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
auto& in = detail::Ref(ctx.Input<framework::LoDTensor>("X"));
auto& w = detail::Ref(ctx.Input<framework::LoDTensor>("W"));
auto* path = ctx.Input<framework::LoDTensor>("PathTable");
auto* code = ctx.Input<framework::LoDTensor>("PathCode");
auto* in_grad =
ctx.Output<framework::LoDTensor>(framework::GradVarName("X"));
auto& in = GET_DATA_SAFELY(ctx.Input<LoDTensor>("X"), "Input", "X",
"HierarchicalSigmoidGrad");
auto& w = GET_DATA_SAFELY(ctx.Input<LoDTensor>("W"), "Input", "W",
"HierarchicalSigmoidGrad");
auto* path = ctx.Input<LoDTensor>("PathTable");
auto* code = ctx.Input<LoDTensor>("PathCode");
auto* in_grad = ctx.Output<LoDTensor>(framework::GradVarName("X"));
bool is_sparse = ctx.Attr<bool>("is_sparse");
auto& dev_ctx = ctx.template device_context<DeviceContext>();
math::SetConstant<DeviceContext, T> zero;
auto& label = detail::Ref(ctx.Input<framework::LoDTensor>("Label"));
auto& pre_out = detail::Ref(ctx.Input<framework::LoDTensor>("PreOut"));
auto& out_grad = detail::Ref(
ctx.Input<framework::LoDTensor>(framework::GradVarName("Out")));
framework::LoDTensor pre_out_grad;
auto& label = GET_DATA_SAFELY(ctx.Input<LoDTensor>("Label"), "Input",
"Label", "HierarchicalSigmoidGrad");
auto& pre_out = GET_DATA_SAFELY(ctx.Input<LoDTensor>("PreOut"), "Input",
"PreOut", "HierarchicalSigmoidGrad");
auto& out_grad = GET_DATA_SAFELY(
ctx.Input<LoDTensor>(framework::GradVarName("Out")), "Input",
framework::GradVarName("Out"), "HierarchicalSigmoidGrad");
LoDTensor pre_out_grad;
pre_out_grad.mutable_data<T>(pre_out.dims(), ctx.GetPlace());
in_grad->mutable_data<T>(ctx.GetPlace());
......@@ -154,11 +161,11 @@ class HierarchicalSigmoidGradOpKernel : public framework::OpKernel<T> {
std::unique_ptr<math::MatrixBitCodeFunctor<T>> bit_code;
if (!is_custom) {
bit_code.reset(new math::MatrixBitCodeFunctor<T>(num_classes,
label.data<int64_t>()));
bit_code.reset(new math::MatrixBitCodeFunctor<T>(
num_classes, label.template data<int64_t>()));
} else {
bit_code.reset(new math::MatrixBitCodeFunctor<T>(*path, *code,
label.data<int64_t>()));
bit_code.reset(new math::MatrixBitCodeFunctor<T>(
*path, *code, label.template data<int64_t>()));
}
// softrelu derivative
......@@ -166,7 +173,7 @@ class HierarchicalSigmoidGradOpKernel : public framework::OpKernel<T> {
auto blas = math::GetBlas<DeviceContext, T>(ctx);
auto* pre_out_grad_data = pre_out_grad.data<T>();
auto* pre_out_data = pre_out.data<T>();
auto* pre_out_data = pre_out.template data<T>();
auto n = pre_out.numel();
blas.VEXP(n, pre_out_data, pre_out_grad_data);
blas.VINV(n, pre_out_grad_data, pre_out_grad_data);
......@@ -174,7 +181,7 @@ class HierarchicalSigmoidGradOpKernel : public framework::OpKernel<T> {
pre_out_grad_data[i] = 1.0 - pre_out_grad_data[i];
}
bit_code->Sub(&pre_out_grad); // the gradient of clip(w * x + b)
auto* out_grad_data = out_grad.data<T>();
auto* out_grad_data = out_grad.template data<T>();
int64_t dim0 = pre_out_grad.dims()[0];
int64_t dim1 = pre_out_grad.dims()[1];
......@@ -184,16 +191,14 @@ class HierarchicalSigmoidGradOpKernel : public framework::OpKernel<T> {
}
// TODO(guosheng): multiply pre_out_grad with subgradient of clipping to
// be consistent with the clipping in forward.
auto* bias_grad =
ctx.Output<framework::LoDTensor>(framework::GradVarName("Bias"));
auto* bias_grad = ctx.Output<LoDTensor>(framework::GradVarName("Bias"));
if (bias_grad) {
bias_grad->mutable_data<T>(ctx.GetPlace());
zero(dev_ctx, bias_grad, static_cast<T>(0.0));
bit_code->AddGrad(pre_out_grad, bias_grad);
}
if (!is_sparse) {
auto* w_grad =
ctx.Output<framework::LoDTensor>(framework::GradVarName("W"));
auto* w_grad = ctx.Output<LoDTensor>(framework::GradVarName("W"));
w_grad->mutable_data<T>(ctx.GetPlace());
zero(dev_ctx, w_grad, static_cast<T>(0.0));
bit_code->MulGradWeight(pre_out_grad, w_grad, in);
......
paddle/fluid/operators/lod_tensor_to_array_op.cc
浏览文件 @ 16315d3d
......@@ -16,7 +16,6 @@ limitations under the License. */
#include "paddle/fluid/framework/lod_rank_table.h"
#include "paddle/fluid/framework/lod_tensor_array.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/math/concat_and_split.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/port.h"
......@@ -95,13 +94,15 @@ class LoDTensorToArrayOp : public framework::OperatorBase {
private:
void RunImpl(const framework::Scope &scope,
const platform::Place &place) const override {
auto &x = detail::Ref(scope.FindVar(Input("X")), "Cannot find input %s",
Input("X"))
auto &x = GET_DATA_SAFELY(scope.FindVar(Input("X")), "Input", "X",
"LoDTensorToArray")
.Get<framework::LoDTensor>();
auto &rank_table = detail::Ref(scope.FindVar(Input("RankTable")))
auto &rank_table = GET_DATA_SAFELY(scope.FindVar(Input("RankTable")),
"Input", "RankTable", "LoDTensorToArray")
.Get<framework::LoDRankTable>();
auto &out = *detail::Ref(scope.FindVar(Output("Out")))
.GetMutable<framework::LoDTensorArray>();
auto &out = *(GET_DATA_SAFELY(scope.FindVar(Output("Out")), "Output", "Out",
"LoDTensorToArray")
.GetMutable<framework::LoDTensorArray>());
auto &items = rank_table.items();
auto max_seq_len = items[0].length;
auto rank_level = rank_table.level();
......
paddle/fluid/operators/matmul_op.cc
浏览文件 @ 16315d3d
......@@ -16,7 +16,6 @@ limitations under the License. */
#include <utility>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/math/blas.h"
namespace paddle {
......@@ -58,10 +57,10 @@ template <typename DeviceContext, typename T>
class MatMulKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext &context) const override {
auto &x =
detail::Ref(context.Input<framework::Tensor>("X"), "Cannot find X");
auto &y =
detail::Ref(context.Input<framework::Tensor>("Y"), "Cannot find Y");
auto &x = GET_DATA_SAFELY(context.Input<framework::Tensor>("X"), "Input",
"X", "MatMul");
auto &y = GET_DATA_SAFELY(context.Input<framework::Tensor>("Y"), "Input",
"Y", "MatMul");
auto *out = context.Output<framework::Tensor>("Out");
out->mutable_data<T>(context.GetPlace());
......
paddle/fluid/operators/mkldnn/mkldnn_activation_op.h
浏览文件 @ 16315d3d
......@@ -17,7 +17,6 @@ limitations under the License. */
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#ifdef PADDLE_WITH_MKLDNN
#include "paddle/fluid/platform/mkldnn_helper.h"
......
paddle/fluid/operators/optimizers/adam_op.cu
浏览文件 @ 16315d3d
......@@ -128,7 +128,6 @@ class AdamOpCUDAKernel : public framework::OpKernel<T> {
framework::ToTypeName(param_var->Type())));
using paddle::framework::LoDTensor;
using paddle::operators::detail::Ref;
int64_t min_row_size_to_use_multithread =
ctx.Attr<int64_t>("min_row_size_to_use_multithread");
......
paddle/fluid/operators/optimizers/adam_op.h
浏览文件 @ 16315d3d
......@@ -20,7 +20,6 @@ limitations under the License. */
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/threadpool.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/math/algorithm.h"
#include "paddle/fluid/operators/math/selected_rows_functor.h"
#include "paddle/fluid/platform/for_range.h"
......@@ -384,7 +383,6 @@ class AdamOpKernel : public framework::OpKernel<T> {
framework::ToTypeName(param_var->Type()));
using paddle::framework::LoDTensor;
using paddle::operators::detail::Ref;
int64_t min_row_size_to_use_multithread =
ctx.Attr<int64_t>("min_row_size_to_use_multithread");
......
paddle/fluid/operators/optimizers/lamb_op.h
浏览文件 @ 16315d3d
......@@ -17,7 +17,6 @@ limitations under the License. */
#include <Eigen/Dense>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/math/algorithm.h"
#include "paddle/fluid/operators/math/selected_rows_functor.h"
#include "paddle/fluid/platform/for_range.h"
......@@ -185,30 +184,32 @@ class LambOpKernel : public framework::OpKernel<T> {
framework::ToTypeName(param_var->Type()));
using paddle::framework::LoDTensor;
using paddle::operators::detail::Ref;
T weight_decay = static_cast<T>(ctx.Attr<float>("weight_decay"));
T beta1 = static_cast<T>(ctx.Attr<float>("beta1"));
T beta2 = static_cast<T>(ctx.Attr<float>("beta2"));
T epsilon = static_cast<T>(ctx.Attr<float>("epsilon"));
auto& param = Ref(ctx.Input<LoDTensor>("Param"), "Must set Param.");
auto& param = GET_DATA_SAFELY(ctx.Input<LoDTensor>("Param"), "Input",
"Param", "Lamb");
auto* grad_var = ctx.InputVar("Grad");
auto& mom1 = Ref(ctx.Input<LoDTensor>("Moment1"), "Must set Moment1.");
auto& mom2 = Ref(ctx.Input<LoDTensor>("Moment2"), "Must set Moment2.");
auto& lr =
Ref(ctx.Input<LoDTensor>("LearningRate"), "Must set LearningRate.");
auto& beta1_pow =
Ref(ctx.Input<LoDTensor>("Beta1Pow"), "Must set Beta1Pow.");
auto& beta2_pow =
Ref(ctx.Input<LoDTensor>("Beta2Pow"), "Must set Beta2Pow.");
auto& param_out =
Ref(ctx.Output<LoDTensor>("ParamOut"), "Must set ParamOut.");
auto& mom1_out =
Ref(ctx.Output<LoDTensor>("Moment1Out"), "Must set Moment1Out.");
auto& mom2_out =
Ref(ctx.Output<LoDTensor>("Moment2Out"), "Must set Moment1Out.");
auto& mom1 = GET_DATA_SAFELY(ctx.Input<LoDTensor>("Moment1"), "Input",
"Moment1", "Lamb");
auto& mom2 = GET_DATA_SAFELY(ctx.Input<LoDTensor>("Moment2"), "Input",
"Moment2", "Lamb");
auto& lr = GET_DATA_SAFELY(ctx.Input<LoDTensor>("LearningRate"), "Input",
"LearningRate", "Lamb");
auto& beta1_pow = GET_DATA_SAFELY(ctx.Input<LoDTensor>("Beta1Pow"), "Input",
"Beta1Pow", "Lamb");
auto& beta2_pow = GET_DATA_SAFELY(ctx.Input<LoDTensor>("Beta2Pow"), "Input",
"Beta2Pow", "Lamb");
auto& param_out = GET_DATA_SAFELY(ctx.Output<LoDTensor>("ParamOut"),
"Output", "ParamOut", "Lamb");
auto& mom1_out = GET_DATA_SAFELY(ctx.Output<LoDTensor>("Moment1Out"),
"Output", "Moment1Out", "Lamb");
auto& mom2_out = GET_DATA_SAFELY(ctx.Output<LoDTensor>("Moment2Out"),
"Output", "Moment2Out", "Lamb");
auto& dev_ctx = ctx.template device_context<DeviceContext>();
platform::ForRange<DeviceContext> for_range(dev_ctx, param.numel());
......@@ -217,7 +218,7 @@ class LambOpKernel : public framework::OpKernel<T> {
// Update moments
if (grad_var->IsType<framework::LoDTensor>()) {
auto& grad = Ref(ctx.Input<LoDTensor>("Grad"), "Must set Grad.");
auto& grad = *ctx.Input<LoDTensor>("Grad");
LambMomentUpdateFunctor<T> moment_update_functor(
weight_decay, beta1, beta2, epsilon, beta1_pow.template data<T>(),
......@@ -229,8 +230,8 @@ class LambOpKernel : public framework::OpKernel<T> {
trust_ratio_div.template data<T>());
for_range(moment_update_functor);
} else if (grad_var->IsType<framework::SelectedRows>()) {
auto& grad =
Ref(ctx.Input<framework::SelectedRows>("Grad"), "Must set Grad.");
auto& grad = GET_DATA_SAFELY(ctx.Input<framework::SelectedRows>("Grad"),
"Input", "Grad", "Lamb");
if (grad.rows().size() == 0) {
VLOG(3) << "grad row size is 0!!";
return;
......
paddle/fluid/operators/random_crop_op.h
浏览文件 @ 16315d3d
......@@ -16,7 +16,6 @@
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/for_range.h"
#ifdef PADDLE_WITH_CUDA
......@@ -152,10 +151,11 @@ class RandomCropKernel : public framework::OpKernel<T> {
public:
virtual void Compute(const framework::ExecutionContext& ctx) const {
int64_t seed = 0;
auto& seed_tensor = detail::Ref(ctx.Input<framework::LoDTensor>("Seed"));
auto& seed_tensor = GET_DATA_SAFELY(ctx.Input<framework::LoDTensor>("Seed"),
"Input", "Seed", "RandomCrop");
if (seed_tensor.IsInitialized()) {
if (platform::is_cpu_place(seed_tensor.place())) {
seed = *seed_tensor.data<int64_t>();
seed = *seed_tensor.template data<int64_t>();
} else {
LOG(WARNING) << "It is slow to place seed in GPU memory. Please verify "
"your program";
......@@ -169,13 +169,15 @@ class RandomCropKernel : public framework::OpKernel<T> {
seed = ctx.Attr<int>("startup_seed");
}
auto shape = ctx.Attr<std::vector<int>>("shape");
auto& x = detail::Ref(ctx.Input<framework::LoDTensor>("X"));
auto& out = detail::Ref(ctx.Output<framework::LoDTensor>("Out"));
auto& x = GET_DATA_SAFELY(ctx.Input<framework::LoDTensor>("X"), "Input",
"X", "RandomCrop");
auto& out = GET_DATA_SAFELY(ctx.Output<framework::LoDTensor>("Out"),
"Output", "Out", "RandomCrop");
int num_batchsize_dims = x.dims().size() - shape.size();
RandomCropFunctor<DeviceContext, T> functor(
x.data<T>(), out.mutable_data<T>(ctx.GetPlace()), x.dims(), out.dims(),
num_batchsize_dims, seed);
x.template data<T>(), out.template mutable_data<T>(ctx.GetPlace()),
x.dims(), out.dims(), num_batchsize_dims, seed);
platform::ForRange<DeviceContext> for_range(
ctx.template device_context<DeviceContext>(),
functor.prod_batchsize_dims_);
......
paddle/fluid/operators/reader/create_custom_reader_op.cc
浏览文件 @ 16315d3d
......@@ -13,7 +13,6 @@
// limitations under the License.
#include "paddle/fluid/framework/executor.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/reader/reader_op_registry.h"
namespace paddle {
......@@ -171,8 +170,11 @@ void CustomReader::ReadNextImpl(std::vector<framework::LoDTensor>* out) {
// 3. Copy LoDTensors from sink variables to out.
out->resize(sink_var_names_.size());
for (size_t i = 0; i < sink_var_names_.size(); ++i) {
const auto& tensor = detail::Ref(exe_scope->FindVar(sink_var_names_[i]))
.Get<framework::LoDTensor>();
auto* var = exe_scope->FindVar(sink_var_names_[i]);
PADDLE_ENFORCE_NOT_NULL(var, platform::errors::NotFound(
"The variable %s is not in current scope.",
sink_var_names_[i]));
const auto& tensor = var->Get<framework::LoDTensor>();
framework::TensorCopySync(tensor, platform::CPUPlace(), &(*out)[i]);
}
scope_.DeleteScope(exe_scope);
......
paddle/fluid/operators/reader/read_op.cc
浏览文件 @ 16315d3d
......@@ -15,7 +15,6 @@
#include "paddle/fluid/framework/framework.pb.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/reader.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/platform/profiler.h"
namespace paddle {
......@@ -96,8 +95,8 @@ class ReadOp : public framework::OperatorBase {
const platform::Place& dev_place) const override {
VLOG(3) << "read op in";
framework::ReaderHolder* reader =
detail::Ref(scope.FindVar(Input("Reader")),
"Cannot find reader variable %s", Input("Reader"))
GET_DATA_SAFELY(scope.FindVar(Input("Reader")), "Input", "Reader",
"Read")
.GetMutable<framework::ReaderHolder>();
std::vector<std::string> out_arg_names = Outputs("Out");
std::vector<framework::LoDTensor> ins;
......
paddle/fluid/operators/reorder_lod_tensor_by_rank_op.cc
浏览文件 @ 16315d3d
......@@ -14,7 +14,6 @@ limitations under the License. */
#include "paddle/fluid/framework/lod_rank_table.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/platform/device_context.h"
namespace paddle {
......@@ -78,18 +77,16 @@ class ReorderLoDTensorByRankTableBase : public framework::OperatorBase {
private:
void RunImpl(const framework::Scope &scope,
const platform::Place &place) const override {
auto &x =
detail::Ref(scope.FindVar(Input("X")),
"Cannot find input lod tensor variable %s", Input("X"))
.Get<framework::LoDTensor>();
auto &rank_table = detail::Ref(scope.FindVar(Input("RankTable")),
"Cannot find input rank table variable %s",
Input("RankTable"))
.Get<framework::LoDRankTable>();
auto &out =
*detail::Ref(scope.FindVar(Output("Out")),
"Cannot find output lod tensor variable %s", Output("Out"))
.GetMutable<framework::LoDTensor>();
auto &x = GET_DATA_SAFELY(scope.FindVar(Input("X")), "Input", "X",
"ReorderLoDTensorByRankTable")
.Get<framework::LoDTensor>();
auto &rank_table =
GET_DATA_SAFELY(scope.FindVar(Input("RankTable")), "Input", "RankTable",
"ReorderLoDTensorByRankTable")
.Get<framework::LoDRankTable>();
auto &out = *(GET_DATA_SAFELY(scope.FindVar(Output("Out")), "Output", "Out",
"ReorderLoDTensorByRankTable")
.GetMutable<framework::LoDTensor>());
out.Resize(x.dims());
out.mutable_data(x.place(), x.type());
......
paddle/fluid/operators/scale_op.cc
浏览文件 @ 16315d3d
......@@ -17,8 +17,6 @@ limitations under the License. */
#include <memory>
#include <string>
#include "paddle/fluid/operators/detail/safe_ref.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/sequence_ops/sequence_concat_op.h
浏览文件 @ 16315d3d
......@@ -18,7 +18,6 @@
#include <vector>
#include "boost/optional.hpp"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#include "paddle/fluid/operators/math/concat_and_split.h"
namespace paddle {
......@@ -47,16 +46,28 @@ inline framework::LoD ConcatLoD(const Container &xs,
lod.emplace_back(result);
return lod;
}
template <typename T, typename... ARGS>
inline std::vector<std::reference_wrapper<T>> GetDataVectorSafely(
const std::vector<T *> &vec, ARGS &&... args) {
std::vector<std::reference_wrapper<T>> result;
result.reserve(vec.size());
for (auto *ptr : vec) {
PADDLE_ENFORCE_NOT_NULL(ptr, platform::errors::InvalidArgument(
"The input variable X contains nullptr."));
result.emplace_back(*ptr);
}
return result;
}
} // namespace detail
template <typename DeviceContext, typename T>
class SeqConcatKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext &context) const override {
auto xs = detail::VectorRef(context.MultiInput<framework::LoDTensor>("X"),
"Cannot find multiple input X");
auto &out = detail::Ref(context.Output<framework::LoDTensor>("Out"),
"Cannot find output");
auto xs = detail::GetDataVectorSafely(
context.MultiInput<framework::LoDTensor>("X"));
auto &out = *context.Output<framework::LoDTensor>("Out");
size_t lod_size = 0;
for (auto &x : xs) {
......@@ -141,9 +152,9 @@ class SeqConcatGradKernel : public framework::OpKernel<T> {
math::SplitFunctor<DeviceContext, T> functor;
functor(context.template device_context<DeviceContext>(),
detail::Ref(
GET_DATA_SAFELY(
context.Input<framework::Tensor>(framework::GradVarName("Out")),
"Sequence Concat OG must be set"),
"Input", framework::GradVarName("Out"), "SeqConcatGrad"),
sliced_x_ptr, 0, &sliced_dx_ptr);
}
};
......
paddle/fluid/operators/sequence_ops/sequence_expand_as_op.h
浏览文件 @ 16315d3d
......@@ -19,7 +19,6 @@ limitations under the License. */
#include <vector>
#include "glog/logging.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/sum_op.cc
浏览文件 @ 16315d3d
......@@ -18,7 +18,6 @@ limitations under the License. */
#include <vector>
#include "paddle/fluid/framework/var_type_inference.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
#ifdef PADDLE_WITH_MKLDNN
#include "paddle/fluid/platform/mkldnn_helper.h"
......
paddle/fluid/platform/enforce.h
浏览文件 @ 16315d3d
......@@ -350,6 +350,51 @@ struct EnforceNotMet : public std::exception {
/** EXTENDED TOOL FUNCTIONS WITH CHECKING **/
/*
* Summary: This macro is used to get Variable or internal type
* data (such as LoDTensor or SelectedRows) of the Input and
* Output in op, generally used when call scope.FindVar(Input/
* Output("Name")) or ctx.Input<LoDTensor>().
* Firstly this macro check whether the obtained pointer is null,
* and then return data if it is not null.
*
* Note: This macro is only suitable for specific scenarios and
* does not intended to be widely used. If it cannot meet the
* requirements, please use other PADDLE_ENFORCE** check macro.
*
* Parameters:
*     __PTR: pointer
* __ROLE: (string), Input or Output
* __NAME: (string), Input or Output name
* __OP_TYPE: (string), the op type
*  
* Return: The data pointed to by the pointer.
*
* Examples:
* GET_DATA_SAFELY(ctx.Input<LoDTensor>("X"), "Input", "X", "Mul");
*/
#define GET_DATA_SAFELY(__PTR, __ROLE, __NAME, __OP_TYPE) \
(([&]() -> std::add_lvalue_reference<decltype(*(__PTR))>::type { \
auto* ptr = (__PTR); \
if (UNLIKELY(nullptr == ptr)) { \
__THROW_ERROR_INTERNAL__( \
"%s\n [Hint: pointer " #__PTR " should not be null.]", \
paddle::platform::errors::NotFound( \
"Unable to get %s data of %s %s in operator %s. " \
"Possible reasons are:\n" \
" 1. The %s is not the %s of operator %s;\n" \
" 2. The %s has no corresponding variable passed in;\n" \
" 3. The %s corresponding variable is not initialized.", \
paddle::platform::demangle( \
typeid(std::add_lvalue_reference<decltype(*ptr)>::type) \
.name()), \
__ROLE, __NAME, __OP_TYPE, __NAME, __ROLE, __OP_TYPE, __NAME, \
__NAME) \
.ToString()); \
} \
return *ptr; \
})())
/*
* Summary: This macro is used to check whether op has specified
* Input or Output Variables. Because op's Input and Output
......
paddle/fluid/platform/enforce_test.cc
浏览文件 @ 16315d3d
......@@ -362,6 +362,22 @@ TEST(enforce, cannot_to_string_type) {
PADDLE_ENFORCE_NE(list.begin(), list.end());
}
TEST(GET_DATA_SAFELY_MACRO, SUCCESS) {
int* a = new int(10);
GET_DATA_SAFELY(a, "Input", "X", "dummy");
}
TEST(GET_DATA_SAFELY_MACRO, FAIL) {
bool caught_exception = false;
try {
int* a = nullptr;
GET_DATA_SAFELY(a, "Input", "X", "dummy");
} catch (paddle::platform::EnforceNotMet& error) {
caught_exception = true;
}
EXPECT_TRUE(caught_exception);
}
TEST(OP_INOUT_CHECK_MACRO, SUCCESS) {
OP_INOUT_CHECK(true, "Input", "X", "dummy");
}
......
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